Table of Contents

Workshop Registration End Date :2025-04-28

Mentor Based

Build Intelligent AI Apps with Retrieval-Augmented Generation (RAG)

Python, Basics of Machine Learning/NLP, REST APIs

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MODE
Virtual / Online

TYPE
Mentor Based

LEVEL
Moderate

DURATION
3 Days

START DATE
28 -April -2025

TIME
5 PM IST

About

Build Intelligent AI Apps with Retrieval-Augmented Generation (RAG) is a cutting-edge international workshop focused on one of the most powerful emerging techniques in AI today. RAG combines the generative power of LLMs with retrieval systems like vector databases to deliver contextually relevant, up-to-date, and verifiable outputs.

Participants will learn to architect and implement RAG pipelines, work with tools like LangChain, Haystack, Pinecone, FAISS, and integrate them with LLMs (OpenAI, Cohere, DeepSeek, or Hugging Face models) for real-world use cases in enterprise automation, research assistants, chatbots, legal tech, and knowledge engines.

Aim

To empower participants with the practical skills and conceptual understanding needed to design, build, and deploy Retrieval-Augmented Generation (RAG) pipelines that combine Large Language Models (LLMs) with dynamic, up-to-date data sources for intelligent, trustworthy AI applications.

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Batches
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Workshop Objectives

Demystify Retrieval-Augmented Generation and its components
Enable real-world implementation with popular AI toolkits
Teach prompt injection prevention, grounding, and retrieval optimization
Stimulate innovation in building knowledge-enhanced LLM apps
Guide participants to build and deploy a fully functional AI app with RAG

Workshop Structure

🔹 Day 1: Introduction & Fundamentals of RAG

Session Title: RAG 101 – Foundation of Retrieval-Augmented Generation

🕐 Time Allocation:

20 min: Welcome, Objectives & Icebreaker
40 min: RAG Conceptual Overview
30 min: Document Stores & Embeddings
30 min: Hands-on – Creating a Basic Vector Store using FAISS/Chroma

🔍 Topics:

Overview of Language Models (LLMs) & Limitations
Why RAG? – Bridging LLMs with External Knowledge
Anatomy of a RAG System: Retriever + Generator
Tools: FAISS, ChromaDB, LangChain, HuggingFace, OpenAI

💻 Hands-on:

Build a vector store using FAISS/Chroma
Embed documents using SentenceTransformers or OpenAI Embeddings

🔹 Day 2: Building the RAG Pipeline

Session Title: Designing the RAG Workflow

🕐 Time Allocation:

30 min: Recap + Theory – Retriever and Generator Flow
45 min: Hands-on – End-to-End RAG using LangChain or Haystack
30 min: Integrating OpenAI/LLama/Anthropic APIs
15 min: Q&A + Assignments

🔍 Topics:

Types of Retrievers: Dense vs Sparse
Query Rewriting, Chunking & Indexing
LangChain vs Haystack vs Custom RAG Pipelines
Prompt Engineering in RAG

💻 Hands-on:

Build a RAG pipeline using LangChain
Query documents and generate contextual answers using GPT

🔹 Day 3: Advanced Features & Deployment

Session Title: Productizing Your RAG Application

🕐 Time Allocation:

30 min: Versioning, Evaluation & Fine-tuning
45 min: Deploying RAG on Streamlit/Gradio
30 min: Integrating Webhooks/APIs
15 min: Demo Presentations & Certificate Distribution

🔍 Topics:

Evaluation Metrics for RAG Systems (EM, BLEU, Recall@k)
Caching, Logging, and Observability
Securing APIs & Cost Management
Open-source RAG use cases (e.g., DocChat, Chat with PDF, Legal AI, Academic Copilots)

💻 Hands-on:

Deploy a working RAG chatbot on Gradio
Custom PDF/CSV Q&A assistant (bring-your-own-data)

Intended For

AI/ML developers and data scientists
Backend or full-stack developers building AI integrations
NLP researchers and LLM enthusiasts
LegalTech, HealthTech, and EdTech innovators
Students with a working knowledge of Python and NLP

Important Dates

Registration Ends

2025-04-28
Indian Standard Timing 3:00 PM

Workshop Dates

2025-04-28 to 2025-04-30
Indian Standard Timing 5 PM

Workshop Outcomes

Master RAG pipeline design and deployment
Learn to embed documents and retrieve relevant context dynamically
Combine search and generation seamlessly for fact-rich AI applications
Build an intelligent AI assistant that can reason over documents or databases
Gain hands-on experience with LangChain, FAISS, Pinecone, and Hugging Face
Receive international workshop certification and reusable project templates

Mentor Profile

DR. CHITRA DHAWALE

Professor

Datta Meghe Institute of Education and Research

Student

INR. 1999
USD. 50

Ph.D. Scholar / Researcher

INR. 2999
USD. 55

Academician / Faculty

INR. 3999
USD. 60

Industry Professional

INR. 5999
USD. 75

We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
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